Paving the way for predictive diagnostics and personalized treatment of invasive aspergillosis

Invasive aspergillosis (IA) is a life-threatening fungal disease commonly diagnosed among individuals with immunological deficits, namely hematological patients undergoing chemotherapy or allogeneic hematopoietic stem cell transplantation. Vaccines are not available, and despite the improved diagnosis and antifungal therapy, the treatment of IA is associated with a poor outcome. Importantly, the risk of infection and its clinical outcome vary significantly even among patients with similar predisposing clinical factors and microbiological exposure. Recent insights into antifungal immunity have further highlighted the complexity of host-fungus interactions and the multiple pathogen-sensing systems activated to control infection. How to decode this information into clinical practice remains however, a challenging issue in medical mycology. Here, we address recent advances in our understanding of the host-fungus interaction and discuss the application of this knowledge in potential strategies with the aim of moving toward personalized diagnostics and treatment (theranostics) in immunocompromised patients. Ultimately, the integration of individual traits into a clinically applicable process to predict the risk and progression of disease, and the efficacy of antifungal prophylaxis and therapy, holds the promise of a pioneering innovation benefiting patients at risk of IA.

Current approaches and future perspectives on strategies for the development of personalized tissue engineering therapies

Personalized tissue engineering and regenerative medicine (TERM) therapies propose patient-oriented effective solutions, considering individual needs. Cell-based therapies, for example, may benefit from cell sources that enable easier autologous set-ups or from recent developments on IPS cells technologies towards effective personalized therapeutics. Furthermore, the customization of scaffold materials to perfectly fit a patientâ s tissue defect through rapid prototyping technologies, also known as 3D printing, is now a reality. Nevertheless, the timing to expand cells or to obtain functional in vitrotissue substitutes prior to implantation prevents advancements towards routine use upon patient´s needs. Thus, personalized therapies also anticipate the importance of creating off-the-shelf solutions to enable immediately available tissue engineered products. This paper reviews the main recent developments and future challenges to enable personalized TERM approaches and to bring these technologies closer to clinical applications.

Urothelial bladder cancer progression: lessons learned from the bench

Urothelial bladder carcinoma (UBC) is an intricate malignancy with a variable natural history and clinical behavior. Despite developments in diagnosis/prognosis refinement and treatment modalities, the recurrence rate is high, and progression from non-muscle to muscle invasive UBC commonly leads to metastasis. Moreover, patients with muscle-invasive or extra-vesical disease often fail the standard chemotherapy treatment, and overall survival rates are poor. Thus, UBC remains a challenge in the oncology field, representing an ideal candidate for research on biomarkers that could identify patients at increased risk of recurrence, progression, and chemo-refractoriness. However, progress toward personalized medicine has been hampered by the unique genetic complexity of UBC. Recent genome-wide expression and sequencing studies have brought new insights into its molecular features, pathogenesis and clinical diversity, revealing a landscape where classical pathology is intersected by the novel and heterogeneous molecular groups. Hence, it seems plausible to postulate that only an integrated signature of prognostic/predictive biomarkers inherent in different cancer hallmarks will reach clinical validation. In this review, we have summarized ours and others' research into novel putative biomarkers of progression and chemoresistance that encompass several hallmarks of cancer: tumor neovascularization, invasion and metastasis, and energy metabolism reprogramming of the tumor microenvironment.

Stromal vascular fraction cell sheets angiogenic potential for tissue engineering and regenerative medicine applications

One of the biggest concerns in the Tissue Engineering field is the correct vascularization of engineered constructs. Strategies involving the use of endothelial cells are promising but adequate cell sourcing and neo-vessels stability are enduring challenges. In this work, we propose the hypoxic pre-conditioning of the stromal vascular fraction (SVF) of human adipose tissue to obtain highly angiogenic cell sheets (CS). For that, SVF was isolated after enzymatic dissociation of adipose tissue and cultured until CS formation in normoxic (pO2=21%) and hypoxic (pO2=5%) conditions for 5 and 8 days, in basal medium. Immunocytochemistry against CD31 and CD146 revealed the presence of highly branched capillary-like structures, which were far more complex for hypoxia. ELISA quantification showed increased VEGF and TIMP-1 secretion in hypoxia for 8 days of culture. In a Matrigel assay, the formation of capillary-like structures by endothelial cells was more prominent when cultured in conditioned medium recovered from the cultures in hypoxia. The same conditioned medium increased the migration of adipose stromal cells in a scratch assay, when compared with the medium from normoxia. Histological analysis after implantation of 8 days normoxic- and hypoxic-conditioned SVF CS in a hindlimb ischemia murine model showed improved formation of neo-blood vessels. Furthermore, Laser Doppler results demonstrated that the blood perfusion of the injured limb after 30 days was enhanced for the hypoxic CS group. Overall, these results suggest that SVF CS created under hypoxia can be used as functional vascularization units for tissue engineering and regenerative medicine.

Predicting plateau pressure in intensive medicine for ventilated patients

Barotrauma is identified as one of the leading diseases in Ventilated Patients. This type of problem is most common in the Intensive Care Units. In order to prevent this problem the use of Data Mining (DM) can be useful for predicting their occurrence. The main goal is to predict the occurence of Barotrauma in order to support the health professionals taking necessary precautions. In a first step intensivists identified the Plateau Pressure values as a possible cause of Barotrauma. Through this study DM models (classification) where induced for predicting the Plateau Pressure class (>=30 cm

Interacting and making personalized recommendations of places of interest to tourists

Advances in Intelligent Systems and Computing, 353

Biological markers in noninvasive brain stimulation trials in major depressive disorder: a systematic review

Objectives: The therapeutic effects of transcranial magnetic stimulation (TMS) and transcranial direct current stimulation in patients with major depression have shown promising results; however, there is a lack of mechanistic studies using biological markers (BMs) as an outcome. Therefore, our aim was to review noninvasive brain stimulation trials in depression using BMs. Methods: The following databases were used for our systematic review: MEDLINE, Web of Science, Cochrane, and SCIELO. We examined articles published before November 2012 that used TMS and transcranial direct current stimulation as an intervention for depression and had BM as an outcome measure. The search was limited to human studies written in English. Results: Of 1234 potential articles, 52 articles were included. Only studies using TMS were found. Biological markers included immune and endocrine serum markers, neuroimaging techniques, and electrophysiological outcomes. In 12 articles (21.4%), end point BM measurements were not significantly associated with clinical outcomes. All studies reached significant results in the main clinical rating scales. Biological marker outcomes were used as predictors of response, to understand mechanisms of TMS, and as a surrogate of safety. Conclusions: Functional magnetic resonance imaging, single-photon emission computed tomography, positron emission tomography, magnetic resonance spectroscopy, cortical excitability, and brain-derived neurotrophic factor consistently showed positive results. Brain-derived neurotrophic factor was the best predictor of patients’ likeliness to respond. These initial results are promising; however, all studies investigating BMs are small, used heterogeneous samples, and did not take into account confounders such as age, sex, or family history. Based on our findings, we recommend further studies to validate BMs in noninvasive brain stimulation trials in MDD.

Personalized-based dietary recommendation for weightlifting

Dissertação de mestrado integrado em Engenharia Eletrónica Industrial e Computadores

Bioactive ceramics for tissue engineering and regenerative medicine derived from marine sponges

Publicado em "Journal of tissue engineering and regenerative medicine". Vol. 8, suppl. s1 (2014)

Zebrafish embryos as in vivo model for toxicity evaluation: screening of nanoparticle formulations DODAB:MO and DODAC:MO

Dissertação de mestrado em Molecular Genetics

Development of a poly(L-Lactic acid) based drug release system

Dissertação de mestrado em Biofísica e Bionanossistemas

Real-Time decision support using data mining to predict blood pressure critical events in intensive medicine patients

Patient blood pressure is an important vital signal to the physicians take a decision and to better understand the patient condition. In Intensive Care Units is possible monitoring the blood pressure due the fact of the patient being in continuous monitoring through bedside monitors and the use of sensors. The intensivist only have access to vital signs values when they look to the monitor or consult the values hourly collected. Most important is the sequence of the values collected, i.e., a set of highest or lowest values can signify a critical event and bring future complications to a patient as is Hypotension or Hypertension. This complications can leverage a set of dangerous diseases and side-effects. The main goal of this work is to predict the probability of a patient has a blood pressure critical event in the next hours by combining a set of patient data collected in real-time and using Data Mining classification techniques. As output the models indicate the probability (%) of a patient has a Blood Pressure Critical Event in the next hour. The achieved results showed to be very promising, presenting sensitivity around of 95%.

Pre-clinical trials for Machado-Joseph Disease: Hypothesis-based and hypothesis-free therapeutic approaches

Tese de Doutoramento em Ciências da Saúde